The gene they found satisfies the genome wide significance threshold for correlation to brain volume, but not for IQ. If you adopt a Bayesian point of view that the gene is already interesting because of the volume association, and *then* test it for IQ association, you get a significant result (p < 0.05, or whatever). But it still needs to be replicated on larger samples.

The whole topic of the statistics of GWAS needs in-depth discussion but I don't have time right now. The genome wide significance threshold of around 1E-8 which has been adopted by the community and by journals is not entirely justifiable, but at least it has a good track record: results of this significance tend to replicate. On the other hand, from a Bayesian perspective we are throwing away a lot of information to ensure that the list of "hits" is nearly 100% bona fide. A hedge fund manager might be happy with a larger list of hits with, say, a 20% error rate. Homework problem: what is the right balance to produce the best black box phenotype predictor?